arXiv · physics/9810018
Estimating probability densities from short samples: a parametric maximum likelihood approach
Abstract
A parametric method similar to autoregressive spectral estimators is proposed to determine the probability density function (pdf) of a random set. The method proceeds by maximizing the likelihood of the pdf, yielding estimates that perform equally well in the tails as in the bulk of the distribution. It is therefore well suited for the analysis short sets drawn from smooth pdfs and stands out by the simplicity of its computational scheme. Its advantages and limitations are discussed.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
T. Dudok de Wit, E. Floriani. 1998-10-12. Estimating probability densities from short samples: a parametric maximum likelihood approach. https://doi.org/10.1103/physreve.58.5115
Cite the original work for its findings. Save a collection to share your selection of sources.